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lifelines

lifelines is a implementation of survival analysis in Python. What benefits does lifelines offer over other survival analysis implementations?

• built on top of Pandas
• internal plotting methods
• simple and intuitive API
• only focus is survival analysis

Contents:

• Quickstart
  • Installation
  • Kaplan-Meier and Nelson-Aalen
  • Getting data in the right format
  • Survival regression
• Introduction to survival analysis
  • Applications
  • Censoring
  • Survival function
  • Hazard curve
• Survival analysis with lifelines
  • Estimating the survival function using Kaplan-Meier
  • Estimating hazard rates using Nelson-Aalen
  • Estimating cumulative hazards using parametric models
  • Other types of censoring
• Survival regression
  • Cox’s proportional hazard model
  • Aalen’s additive model
  • Cox’s time varying proportional hazard model
  • Model selection in survival regression
• Testing the proportional hazard assumptions
  • Checking assumptions with check_assumptions
• Assessing Cox model fit using residuals (work in progress)
  • Martingale residuals
  • Deviance residuals
• Piecewise Exponential models and creating custom models
  • The Exponential model
  • Piecewise Exponential models
  • Univarite models in lifelines
  • Defining our own survival models
  • Why fit parametric models anyways?
  • Looking for more examples of what you can build?
• Time-lagged conversion rates and cure models
  • Custom parametric models to handle asymptotes
• More examples and recipes
  • Statistically compare two populations
  • Model selection using lifelines
  • Plotting multiple figures on a plot
  • Plotting options and styles
  • Transforming survival-table data into lifelines format
  • Transforming observational data into survival-table format
  • Set the index/timeline of a estimate
  • Example SQL query to get survival data from a table
  • Example SQL queries and transformations to get time varying data
  • Example cumulative sums over time-varying covariates
  • Sample size determination under a CoxPH model
  • Power determination under a CoxPH model
  • Problems with convergence in the Cox proportional hazard model
  • Adding weights to observations in a Cox model
  • Correlations between subjects in a Cox model
• lifelines reference
  • lifelines.fitters
  • lifelines.utils
  • lifelines.plotting
  • lifelines.datasets
• Changelog
  • 0.18.6
  • 0.18.5
  • 0.18.4
  • 0.18.3
  • 0.18.2
  • 0.18.1
  • 0.18.0
  • 0.17.5
  • 0.17.4
  • 0.17.3
  • 0.17.2
  • 0.17.1
  • 0.17.0
  • 0.16.3
  • 0.16.2
  • 0.16.1
  • 0.16.0
  • 0.15.4
  • 0.15.3
  • 0.15.2
  • 0.15.1
  • 0.15.0
  • 0.14.6
  • 0.14.5
  • 0.14.4
  • 0.14.3
  • 0.14.2
  • 0.14.1
  • 0.14.0
  • 0.13.0
  • 0.12.0
  • 0.11.3
  • 0.11.2
  • 0.11.1
  • 0.11.0
  • 0.10.1
  • 0.10.0
  • 0.9.4
  • 0.9.2
  • 0.9.1
  • 0.9.0
  • 0.8.1
  • 0.8.0
  • 0.7.1
  • 0.7.0
  • 0.6.1
  • 0.6.0
  • 0.5.1
  • 0.5.0
  • 0.4.4
  • 0.4.3
  • 0.4.2
  • 0.4.1.1
  • 0.4.1
  • 0.4.0

Installation

pip install lifelines

Source code and issue tracker

Available on Github, CamDavidsonPilon/lifelines. Please report bugs, issues and feature extensions there. We also have Gitter channel avaiable to discuss survival analysis and lifelines:

Citing lifelines

The following link will bring you to a page where you can find the latest citation for lifelines:

Citation for lifelines

Indices and tables

• Index
• Module Index
• Search Page